Senior Data & Analytics Architect

Job Description

Position Overview

Role: Senior Data & Analytics Architect

Location: Toronto ON

Contract

Role

Our delivery is looking for a Senior Data & Analytics Architect to lead the development of next-generation cloud-native data and AI platforms. This role is pivotal in shaping scalable Lakehouse architectures and enabling enterprise-wide analytics, machine learning and generative AI capabilities. Technologies like Azure, AWS, Databricks and Unity Catalog to drive innovation and deliver measurable business impact.

Cloud & Lakehouse Architecture

• Architect and deploy Lakehouse platforms using Databricks on Azure, Delta Lake, Apache Spark and ADLS Gen2.
• Build and optimize data pipelines with Databricks Workflows and Azure Data Factory for structured and unstructured data.
• Implement secure, compliant data governance and lineage using Unity Catalog.
• Enable real-time and batch analytics with Databricks Structured Streaming, Azure Event Hubs and Amazon Kinesis.
• Design, build and maintain scalable data pipelines and workflows using Azure Data Factory and Databricks leveraging Spark / PySpark frameworks.

Machine Learning & Generative AI

• Collaborate with data science teams to deploy ML and GenAI models using Databricks ML.
• Design solutions for LLM fine-tuning and deployment via Databricks Model Serving, Azure OpenAI and Amazon Bedrock.
• Manage feature stores, model registries and experiment tracking with MLflow and cloud-native MLOps tools.
• Ensure production-grade scalability, monitoring and governance of models.

MLOps & Platform Engineering

• Develop CI / CD pipelines for ML and data workflows using Databricks Repos, Azure DevOps and GitHub Actions.
• Automate workflows with Databricks Jobs and Azure ML Pipelines.
• Optimize compute infrastructure (Databricks clusters, AKS, EKS) for training and inference.
• Implement observability and model drift detection with Databricks monitoring and Azure Monitor.

Strategic Leadership

• Translate business goals into scalable data and AI solutions in partnership with both business and technical stakeholders.
• Mentor data engineers, ML engineers and analytics professionals.
• Evaluate and recommend emerging GenAI frameworks and cloud-native tools.
• Champion data democratization and self-service analytics with Power BI and Databricks SQL.

Resource Profile

• Bachelors or Masters in Computer Science, Data Engineering or related field.
• 8 years of experience in data architecture, engineering or analytics.
• Preferred certifications: Databricks Certified Data Engineer or Architect; Azure Solutions Architect Expert; AWS Certified Solutions Architect; Azure or AWS Machine Learning Specialty.
• Deep expertise in Databricks Unity Catalog, Azure and/or AWS data and ML services.
• Strong grasp of Lakehouse architecture, data governance and MLOps.
• Hands-on experience with Databricks Unity Catalog, MLflow, LLMs and GenAI frameworks.
• Proven proficiency in Databricks including building pipelines and workflows and a solid understanding of Spark / PySpark.
• Expertise with Azure Data Factory, Databricks SQL data pipeline development and Power BI reporting.
• Excellent communication and stakeholder engagement skills.

Key Skills

• Fund Management
• Drafting
• End User Support
• Infrastructure
• Airlines
• Catia

Employment Type

Full-time

Experience

years

Vacancy

1